Re-visualization Project

Introduction:

Suicide is the act of intentionally causing one’s own death. It can be due to many conditions or the situations. It includes Mental disorders, physical disorders, and substance abuse are the risk factors. Suicides resulted in 828,000 deaths globally in 2015, an increase from 712,000 deaths in 1990. This makes suicide the 10th leading cause of death worldwide. Every death from suicide is a tragedy.

The below is the Visualization on Suicides by Saloni Dattani, Lucas Rodes-Guirao, Hannah Ritchie, Max Roser, and Esteban Ortiz-Ospina. The research shows that suicide rates can be reduced with greater understanding and support. To do that the researchers considered or recognized suicide as a public health problem, and people should know that it can be prevented and its rates can be reduced.

OLD VISUALIZATION:

Suicide rates vary around the world:

Suicide rates vary widely between the countries. The given visualization depicts the data of annual suicide rates per 100,000 people from 1950 to 2022, across various countries. Researchers used line graph to predict the data.

  • X-axis represents the years from 1950 to 2022 and y-axis represents the suicide rate per 100000 people, ranging from 0 to 40. It also says that higher the value, the greater will be the number of suicide rates.

  • Each line of the graph represents the countries. The countries which have higher suicide rates are represented on the top. The legends taken are countries.

Observations:

  • There is a wide range of variations between the countries. Countries like Lithuania, South Korea shows the highest suicide rates, as indicated by their position near the top of the graph.

  • Some countries shows large fluctuations in the suicide rates while other countries shows the constant rate throughout the years.

  • It also says that suicide deaths are under-reported in many countries due to social stigma and culture or legal concerns means that actual rates can be higher than the reported rates.

  • The data is collected based on the data listed in the death certificates. It can impact the accuracy of the data

  • The data is adjusted for age standardization allowing a fair comparison between the countries with different age structures, ensuring that population age distribution doesn’t skew the data.

Bad Visualization Predictions:

  • More number of lines: The graph contains a huge number of lines which are representing the countries. This creates a messy graph it is very difficult to predict the data immediately as we look into the graph.

  • Color Categorization: All the countries represented with different colors but for some countries there are distinct colors where it will be very difficult to categorize the data. There are similar colors in for different countries. We can use more contrasting colors to represent the data or we can group the colors into regions or categories.

  • Interactive Labeling: With so many lines we cannot identify the particular country instantly and it is impossible to find the particular country and there are all the countries mentioned in the legend where it is impossible to identify the specific country. Hence we can use interactive Labeling for highlighting the particular country.

  • No Highlights on the key insights: All the lines in the graph are in equal size where there is no differentiation between the countries. We can highlight the countries which have highest suicide rates and lowest suicide rates with different dimensions of the lines.

The above visualization tells us about the reported suicide rates by age in the United States.

Observations:

It explains the breakdown for the rate of suicides for different age groups like children, adults. The data highlights the trends such as the increasing or decreasing risk of suicide within the specific age over time and across different regions.

  • It shows the data for the suicide rates per 100,000 people across different age groups. Age specific data usually reveals trends showing which age group are more vulnerable to suicide in different regions.

  • According to the graph it predicts that the old generation people have the higher suicide rates (Age between 80-84). The age between 15-19 suicidal rates are less. But there is growing concern about suicidal rates in young adults particularly due to health conditions and mental stress.

Bad Visualization Predictions:

  • More number of lines: The graph contains a huge number of lines which are representing the different age groups. This creates a messy graph it is very difficult to predict the data immediately as we look into the graph.

  • Color Categorization: All the age groups are represented with different colors but for some there are distinct colors where it will be very difficult to categorize the data. There are similar colors for different age groups. We can use more contrasting colors to represent the data or we can group the colors into categories or age groups.

  • Legend: The legend have too many entries where it is difficult for the user to identify the particular data of the age group in a particular year. Viewers must constantly shift their focus on the legend and the graph simultaneously where it would be difficult for predicting the exact information.

  • Lack of data insights: There is no contextual information or annotations on the graph to explain significant spikes, trends or sudden drops in the suicide rates for certain age groups.

  • Interactive Labeling: Adding the interactvite labeling helps to improve the readability.

According to the above research and bad visualizations found we have made some changes and re-visualized the data as below:

Each map or graph in this project displays suicide rates per 100,000 people to enhance the clarity and effectiveness of the visualization and this is the standard that data analysts generally follow while visualizing death related data.

Average Suicidal Rates By Country from 1950 to 2022:

The map below illustrates the average suicide rates by country from 1950 to 2022, broken down by different age groups such as children, young adults, and adults across all nations.

In the previous visualization, the data was presented in a line graph for all countries, resulting in a cluttered and hard-to-read display. To improve clarity, we have re-visualized the data by focusing on the average suicide rates from 1950 to 2022 using a world map. In the provided dataset, we calculated the average suicide rates over the years and made predictions based on that data. The world map offers an easier and more intuitive way to interpret the data. This updated map is also interactive, allowing users to highlight specific parameters and explore the average range of deaths by suicide more flexibly.

Based on the predictions shown in the map, Russia has the highest average suicide rates.

Average Suicide Rates of all the ages by Country for the top rated: 1982

The map below shows the average suicide rates for all age groups by country for the year 1982, which was chosen because it had the highest suicide rates between 1982 and 2022.

In the previous visualization, the data was displayed in a line graph, resulting in a cluttered and hard-to-read format. To improve accessibility, we re-visualized the data by calculating the average suicide rates across all years and selected 1982 for its peak in suicide rates.

This updated visualization uses a world map to display the data, with countries categorized by different colors, highlighting the highest suicide rates in red. Russia stands out as having the highest average suicide rates.

Average Suicide Rates by Year all over the World:

The map below shows the average suicide rates by year globally from 1950 to 2022. We re-visualized the data by calculating the average death rates over this period. First, we determined the averages for each year for all the countries, and then we used a frequency polygon graph to visualize the trend of the suicide rates over all the years.

In this representation, the highest suicide rate occurred in 1982, with a rate of 12.38, while the lowest rate across all countries and age groups was recorded in 2016 with 7.21.

Top 5 Years with Highest Suicide Rates in Top 5 Countries:

The graph below shows the top 5 years with the highest suicide rates in the top 5 countries. First, we identified the 5 countries with the highest average suicide rates. After filtering the data to include only these countries, we selected the top 5 years with the highest suicide rates for each. Using this categorized data, we created a bar graph with ggplot. Additionally, we added interactive labeling to enhance accessibility and provide a more user-friendly experience for viewers.

Average Suicide Rates for Age 15-19 over the years:

The graph below displays the average suicide rates for individuals aged 15-19. The previous visualization focused on overall suicide rates across all years and age groups. For this re-visualization, we specifically selected the 15-19 age group, as it marks the end of teen years. We used a world map to represent the data and incorporated interactive labeling for easier interpretation.

Average Suicide Rate for the Top 20 Nations in the 15-19 Age Group (Across All Years):

The graph below illustrates the average suicide rate for the top 20 countries in the 15-19 age group across all years. It highlights the top 20 countries for this age group, with the addition of interactive labeling for enhanced user experience.